Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
-
systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
-
agents Experience developing infrastructure for machine learning workflows Experience contributing to open data platforms or large scientific databases Awareness of diversity and equal opportunity issues
-
measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
-
complex or high-dimensional systems. Experience with physics-informed or constraint-based machine learning (e.g. neural ODEs, energy-based models) Experience with dynamical systems, stochastic processes
-
algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
-
microscopy, image analysis: Development of microscopes, fluidics, and data analysis pipelines used to acquire and quantify high-throughput binding data. Examples of suitable backgrounds: Optical engineering